Considerations for Rapidly Converging Genetic Algorithms Designed for Application to Problems with Expensive Evaluation Functions

A genetic algorithm is a technique designed to search large problem spaces using the Darwinian concepts of evolution. Solution representations are treated as living organisms. The procedure attempts to evolve increasingly superior solutions. As in natural genetics, however, there is no guarantee that the optimum organism will be produced. One of the problems in producing optimal organisms in a genetic algorithm is the difficulty of premature convergence. Premature convergence occurs when the organisms converge in similarity to a pattern which is sub-optimal, but insufficient genetic material is present to continue the search beyond this sub-optimal level, called a local maximum. The prevention of premature convergence of the organisms is crucial to the success of most genetic algorithms. In order to prevent such convergence, numerous operators have been developed and refined. All such operators, however, rely on the property of the underlying problem that the evaluation of individuals is a computationally inexpensive process. In this paper, the design of genetic algorithms which intentionally converge rapidly is addressed. The design considerations are outlined, and the concept is applied to an NP-Complete problem, known as a Crozzle, which does not have an inexpensive evaluation function. This property would normally make the Crozzle unsuitable for processing by a genetic algorithm. It is shown that a rapidly converging genetic algorithm can successfully reduce the effective complexity of the problem

Webcrow: A web-based system for crossword solving

Language games represent one of the most fascinating challenges of research in artificial intelligence. In this paper we give an overview of WebCrow, a system that tackles crosswords using the Web as a knowledge base. This appears to be a novel approach with respect to the available literature. It is also the first solver for non-English crosswords and it has been designed to be potentially multilingual. Although WebCrow has been implemented only in a preliminary version, it already displays very interesting results reaching the performance of a human beginner: crosswords that are “easy ” for expert humans are solved, within competition time limits, with 80 % of correct words and over 90 % of correct letters

An approach to user-directed search in interactive problem solving

This thesis studies some problems which are important in establishing interactive problem solving systems. An interactive problem solving system is characterized by the intensive interaction between the user and the system. In order to converge on a solution which satisfies the user, we present a new problem solving scheme - user-directed search (UDS) - where the solution search is directed in a step-by-step manner by the user. Because of its wide applicability, UDS can be very useful for many practic~l cases. The user-directed problem solving is realized by introducing a particular communication mechanism between the user and the system. This enables a user to guide the solution searching in his most preferred directions. Thus the system can first explore the solutions which are more likely to match the user-desired solution. We have developed UDS using two different approaches. In the first approach, additional deduction rules can be created upon the user's request and/or upon changes in practical environments. For this purpose, we have created, in the user interface, an environment which enables a user to add his new requirements in the form of deduction rules. To improve efficiency, we have used a particular backjump search which can first find, and then backjump to, the point which contradicts the user's new requirements. To establish the dependency for this backjumping, we have used assumption-based truth maintenance systems (ATMS) and KEEworlds in the knowledge engineering environment(KEE). In the second approach, we have introduced particular variable groups. In this approach, the user's new requirements are introduced through a scheme in which the user divides the variable set into several different variable groups. By dividing these variable groups according to his choice, a user can effectively control and instruct the search during the process of problem solving. We have introduced here a scheme which we call proximal minimum (closeness) change. The proximal minimum change ensures that, in the direction specified by the user, a closest solution to the previous one will be found if it actually exists. In another aspect, in order to improve efficiency of solution search on a general basis, we have applied some techniques from Constraint Satisfaction Problems (CSP) in establishing non-CSP expert systems, e.g. rule-based and frame-structured expert systems on KEE. We find that these CSP techniques can be used to improve efficiency by performing consistency checking prior to searching for a solution, which we call pre-processing. This pre-processing is introduced to eliminate a number of variable values which are inconsistent with certain unary and binary constraints. In practical applications, this method can be used to avoid a considerable amount of useless backtracking. We have developed an independent module for applying CSP techniques in general purpose programming in KEE. This CSP module provides KEE with ability to establish more versatile expert systems. Through case studies of the truck dispatching problem and the word puzzle problem, we demonstrate how to achieve UDS and how to implement various techniques which we have presented to improve efficiency in UDS. Some of the advantages of UDS are shown in the case studies

Methods for Parallelizing Search Paths in Phrasing

Many search problems are commonly solved with combinatoric algorithms that unnecessarily duplicate and serialize work at considerable computational expense. There are techniques available that can eliminate redundant computations and perform remaining operations concurrently, effectively reducing the branching factors of these algorithms. This thesis applies these techniques to the problem of parsing natural language. The result is an efficient programming language that can reduce some of the expense associated with principle-based parsing and other search problems. The language is used to implement various natural language parsers, and the improvements are compared to those that result from implementing more deterministic theories of language processing

Constraint-based Programming: A Survey

Report on constraint-based computer programming analyzing finite-domain and continuous-domain constraint satisfaction methods and existing systems which apply constraints to problem-solving, modeling, and simulation

Selecting and Generating Computational Meaning Representations for Short Texts

Language conveys meaning, so natural language processing (NLP) requires representations of meaning. This work addresses two broad questions: (1) What meaning representation should we use? and (2) How can we transform text to our chosen meaning representation? In the first part, we explore different meaning representations (MRs) of short texts, ranging from surface forms to deep-learning-based models. We show the advantages and disadvantages of a variety of MRs for summarization, paraphrase detection, and clustering. In the second part, we use SQL as a running example for an in-depth look at how we can parse text into our chosen MR. We examine the text-to-SQL problem from three perspectives—methodology, systems, and applications—and show how each contributes to a fuller understanding of the task.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/143967/1/cfdollak_1.pd

Audiolingual method to improve speaking skills in 8th level students at Víctor Manuel Guzmán High School in the academic year 2021-2022

Determine how audiolingual method can influence to the development of speaking skills.Actualmente el idioma inglés es un idioma global hablado en todo el mundo. El idioma inglés proporciona nuevas oportunidades en el campo educacional, comercial y tecnológico. La importancia de hablar este lenguaje es vital mediante este lenguaje las personas pueden desarrollar habilidades efectivamente. Adquirir un lenguaje nuevo es un arduo trabajo, pero sabemos que mediante metodologías las personas pueden desarrollar un aprendizaje significativo para dominar el idioma. Un método eficiente para lograr esto es el método Audio lingual. Este método está enfocado en mejorar el desempeño del estudiante mediante la gramática, fluidez y una efectiva pronunciación. Además, este método contribuye para adquirir un amplio vocabulario mediante patrones gramaticales. Esta investigación es desarrollada para el uso del método Audio lingual para mejorar la habilidad del habla en aprendices del idioma inglés. Esta investigación fue aplicada para los estudiantes de 8vo nivel del colegio Víctor Manuel Guzmán para mejorar el nivel de inglés en los estudiantes, usando un método estructurado apto para transformar el proceso de aprender el idioma. El enfoque de esta investigación es cualitativa, basada en un diseño descriptivo para describir el proceso continuo de la enseñanza y aprendizaje del idioma inglés.Licenciatur